Abstract Despite the association between the levels of CSF A?42, tau, phosphorylated tau and underlying AD pathology, measures of biomarker accuracy for clinical diagnosis vary widely between studies. Given that other neurodegenerative conditions can present with AD-like clinical symptoms, and individuals with AD frequently have comorbid pathologies, additional markers are needed that can aid in differential diagnosis and identify mixed pathologies. Over the last decade, many candidate biomarkers have been identified, reflecting a range of pathophysiological processes including cholesterol metabolism, neuroinflammation and amyloid processing. However, few, have been adopted in clinical practice or been validated in large independent cohorts1. The MacCoss lab and others have been pioneering the development of next generation proteomics methods as an alternative to the classic stochastic mass spectrometry-based methods. These new methods offer a hybrid between a targeted and global proteomics strategy. While mass spectrometry data is collected in an unbiased way, the data is analyzed in a targeted strategy where specific peptides, albeit 1000s are analyzed using prior information. Thus, the reproducible targeting, throughput, and confident MS/MS-based quantification of parallel reaction monitoring (PRM) can be combined with classical discovery methods' ability to qualitatively detect thousands of proteins. These new methods based on systematically collected mass spectrometry data can offer similar quantitative figures of merit and can be validated in analogous fashion to clinical assays. Despite advances in proteomics technologies, most attempts at discovering new CSF markers have either used 1) stochastic sampling methods (e.g. data dependent acquisition) with poorly characterized quantitative performance, 2) small sample cohorts, 3) focused entirely on total CSF, 4) ignored protein processing, and 5) did not consider protein misfolding or stability. The purpose of this project within the cooperative research program is to take our methods to another level ? apply true quantitative methods to large well characterized cohorts and extend them to functionally relevant subpopulations. We have a CSF assay that can measure >1050 proteins from completely unfractionated material with figures of merit of within/between day precision, linearity, LOD/LOQ, etc... Furthermore, we can use this assay on subsets of the CSF proteome to assess functionally relevant aspects of the neurobiology including quantity as part of solution or CSF particles, intact protein MW, and protein stability. Finally, we have enough throughput to apply these analyses on a scale sufficient to eliminate the chance that an observation is due to an aberrant subpopulation.